Title :
The fault character of the motors identified based wavelet transform
Author :
Wang, Xiu-qing ; Feng, L.V. ; Du, Hai-lian ; Dai, Guang-jin
Author_Institution :
Dept. of Electr. Eng., Hebei Normal Univ., China
Abstract :
Based on the contrasting of the basic characteristics wavelet transform, this paper studies the method about getting the fault information by the singularity of the signals identified by wavelet, and the simulation from the computer for the fault signal model of the motors proves that the wavelet transform cannot only separate noise from the useful signal effectively, but also reflect the character and the time when the fault appears.
Keywords :
electric motors; fault diagnosis; interference suppression; signal processing; wavelet transforms; fault identification; motor fault characters; noise separation; wavelet transform; Continuous wavelet transforms; Fault diagnosis; Frequency domain analysis; Signal analysis; Signal processing; Signal resolution; Time frequency analysis; Wavelet analysis; Wavelet domain; Wavelet transforms;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259911
